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» Compressive Sampling Vs. Conventional Imaging
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ICISP
2010
Springer
13 years 9 months ago
Total Variation Minimization with Separable Sensing Operator
Compressed Imaging is the theory that studies the problem of image recovery from an under-determined system of linear measurements. One of the most popular methods in this field i...
Serge L. Shishkin, Hongcheng Wang, Gregory S. Hage...
CORR
2010
Springer
95views Education» more  CORR 2010»
13 years 6 months ago
Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
Guoshen Yu, Guillermo Sapiro
ECCV
2008
Springer
14 years 8 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
PERCOM
2010
ACM
13 years 4 months ago
Resilient image sensor networks in lossy channels using compressed sensing
—Data loss in wireless communications greatly affects the reconstruction quality of a signal. In the case of images, data loss results in a reduction in quality of the received i...
Scott Pudlewski, Arvind Prasanna, Tommaso Melodia
TCSV
2008
341views more  TCSV 2008»
13 years 6 months ago
H.264-Based Compression of Bayer Pattern Video Sequences
Most consumer digital cameras use a single light sensor which captures color information using a color filter array (CFA). This produces a mosaic image, where each pixel location c...
Colin Doutre, Panos Nasiopoulos, Kostas N. Platani...